• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.12
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• pp.2398-2405
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• 2007

This paper proposes a contrast enhancement technique which stretches the intensity surfaces of image to improve the quality of the digital photos. The proposed method enhances the contrast of image by stretching the intensity surface of the original image to the maximum range of the output image in proportion to the distances between the original intensity surface and upper, lower intensity surface, respectively. The upper and lower intensity surfaces are generated from the original intensity surface by gaussian smoothing. In the experiments, digital color images in a variety of illumination conditions were used and the proposed method was compared with other several existed image enhancement algorithms, which are histogram stretching, surface stretching, histogram equalization, gamma correction and retinex. It was proved that the experimental results were more natural visually without deterioration of gradation.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1995.06a
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• pp.69-74
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• 1995

An object color can be seen differently under the various outer illuminants. However, human visual system has color constancy that the object color can be seen constantly under the different outer illuminants. When the viewer watches TV under specific outer illuminants, he perceives distorted color due to the emitting spectrum of outer illuminants as well as the radiation of CPT itself. Namely, when the outer illuminants such as fluorescent and incandescent lamps incident on CPT, brightness, saturation, hue, and contrast on color pictures are changed, he perceives distorted color from the original color. In this paper color enhancement algorithm based on light intensity and outer light decision function using RGB sensor was proposed. The implemented TV of proposed algorithm has higher visual quality at the view point of human visual system and more vivid than that of conventional color TV.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.3
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• pp.525-532
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• 2018

Recently, due to the advancements of sensor network technologies and camera technologies, there are increasing needs to effectively monitor the environment in a region that is difficult to access by using the visual sensor network that combines these two technologies. Since the image captured by the visual sensor reflects the natural phenomenon as it is, the quality of the image may deteriorate depending on the weather or time. In this paper, we propose an algorithm to improve the contrast of images using the characteristics of images obtained from visual sensors. In the proposed method, we first set the region of interest and then analyzes the change of the color value of the region of interest according to the brightness value of the image. The contrast of an image is improved by using the high contrast image of the same object and the analysis information. It is shown by experimental results that the proposed method improves the contrast of an image by restoring the color components of the low contrast image simply and accurately.

• Proceedings of the IEEK Conference
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• 2002.06d
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• pp.251-254
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• 2002

Currently many devices reproduce electronic images in a variety of ways. However, the colors that are reproduced are different from the original color due to the differences in the gamut between devices. In this paper, a gamut mapping method utilizing a simultaneous mapping function and a lightness rescaling is proposed. This method enhance the local-color characteristics and lightness contrast. The experimental result shows that the overall contrast and the colorfulness were increased.

• Journal of the Optical Society of Korea
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• v.15 no.1
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• pp.38-43
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• 2011

We have developed a simple model of a bright-room contrast ratio (BRCR) measurement system for plasma display panels (PDPs) adopting a contrast enhancement film (CEF) by using an illumination design tool. Only four model parameters were used, namely, total ambient illumination power delivered by fluorescent lamps, a panel scattering rate, illuminance of PDP white patterns, and the absorption coefficient of a color adjusting film. These parameters were determined by simple optical measurements and matching simulations. The proposed model was employed to predict the BRCR values of four different CEF samples, and the simulated ones were found to be in agreement with measured ones within about 10% relative-error.

• Analytical Science and Technology
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• v.31 no.5
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• pp.195-200
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• 2018

Researchers have used the visual criteria to compare the effectiveness of fingerprint enhancement techniques. However, since the visual criteria is subjective, bias can occur. Therefore, many researchers have tried to make the criteria objective using the contrast index (CI). However, there is a constraint that the CI was only validated on inked fingerprints or color-change fingerprints. In this study, we compared enhancement of fluorescence fingerprints on colored papers using the CI. The CI values differ according to the color of the background, reagent, and light source, even though the same standard fingerprints were used. Through the comparison of values, we could compare the enhancement of fluorescence fingerprints according to these factors. When visual evaluation criteria were used, the same peak score was obtained regardless of the reagent and light source. However, we could get a more detailed score comparison in this study using the CI. Therefore, it is confirmed that for comparison of enhancement of fluorescence fingerprints, the CI can be used as a basis for determining which light source and reagent are appropriate according to the background.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.4
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• pp.467-472
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• 2005

The principal objective of enhancement methods is to process an image so that the output image is more suitable than the original image lot a specific application. Images taken in the night can be low-contrast images because of poor environments. In this paper, we compared the performance of Image Contrast Enhancement Technique Using Clustering Algorithm(ICECA) with those of color adjustment methods such as Histogram Equalization(HE), Brightness Preserving Bi-Histogram Equalization(BBHE), and the Multi-Scale Refiner(MSR). We compared these methods by applying the image enhancement methods to a set of diverse images.

• Journal of Broadcast Engineering
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• v.15 no.3
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• pp.368-379
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• 2010

As high-definition video is broadly used in various system such as broadcast system and digital camcorder the proper method in order to improve the quality of high-definition video is needed. In this paper, we propose an efficient method to improve color and contrast of high-definition video. In order to apply the image enhancement method to high-definition video, scale-down video of high-definition video is used and the parameter for image enhancement method is computed from small size video. To enhance the color of high-definition video, we apply color constancy method. First, we separate the video into several scenes by cut detection method. Then, we apply color constancy to each scene with same parameter. To improve the contrast of high-definition video, we use union of original image and histogram equalized image, and weight is calculated based on sorting of histogram bins. Finally, the performance of proposed method is demonstrated in experiment section.

• Journal of the Korean Institute of Navigation
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• v.21 no.1
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• pp.119-128
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• 1997

Nowadays, many satellites regularly produce digital multispectral images of the earth's surface. Multispectral images may be displayed as color pictures by selecting three components for assignment to the primary colors. It is desired to enhance these images to generate a display picture that are representativde of their features. in this paper, a false color image processing algorithm is proposed for the purpose of enchancement of the multispectral images based on the human perception. The mean of each primary component is transformed to equalo. Intensity and saturation are enhanced by modified piecewise linear contrast strectching and saturation enhancement method. The proposed method has been successfully applied the LANDSAT TM image and shows good enhancement.

• Journal of Ocean Engineering and Technology
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• v.36 no.1
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• pp.32-40
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• 2022

Underwater optical images face various limitations that degrade the image quality compared with optical images taken in our atmosphere. Attenuation according to the wavelength of light and reflection by very small floating objects cause low contrast, blurry clarity, and color degradation in underwater images. We constructed an image data of the Korean sea and enhanced it by learning the characteristics of underwater images using the deep learning techniques of CycleGAN (cycle-consistent adversarial network), UGAN (underwater GAN), FUnIE-GAN (fast underwater image enhancement GAN). In addition, the underwater optical image was enhanced using the image processing technique of Image Fusion. For a quantitative performance comparison, UIQM (underwater image quality measure), which evaluates the performance of the enhancement in terms of colorfulness, sharpness, and contrast, and UCIQE (underwater color image quality evaluation), which evaluates the performance in terms of chroma, luminance, and saturation were calculated. For 100 underwater images taken in Korean seas, the average UIQMs of CycleGAN, UGAN, and FUnIE-GAN were 3.91, 3.42, and 2.66, respectively, and the average UCIQEs were measured to be 29.9, 26.77, and 22.88, respectively. The average UIQM and UCIQE of Image Fusion were 3.63 and 23.59, respectively. CycleGAN and UGAN qualitatively and quantitatively improved the image quality in various underwater environments, and FUnIE-GAN had performance differences depending on the underwater environment. Image Fusion showed good performance in terms of color correction and sharpness enhancement. It is expected that this method can be used for monitoring underwater works and the autonomous operation of unmanned vehicles by improving the visibility of underwater situations more accurately.